1. Field of the Invention
The present invention relates to an object recognition apparatus, object recognition method, learning apparatus, learning method, storage medium, and information processing system.
2. Description of the Related Art
In the field of object recognition that use visual information, various studies and developments have been made in association with problems to estimate a three-dimensional (3D) position and orientation of an object. In the field of industrial robots or experimental humanoid robots, 3D information is often used for the purpose of, for example, random picking, and its necessity becomes higher.
As for a target object with a given shape, position/orientation estimation of the target object using a monocular camera is also executed. As one 3D orientation estimation method using the monocular camera, a method of identifying various orientations as different classes is known. Also, a method of using 3D feature amounts obtained using a stereo camera or 3D sensor such as a laser rangefinder is known. In this method, a correspondence relationship between a plurality of feature points on a model and 3D feature amounts is calculated, and a position and orientation of an object are calculated using rigid transform. In a target object recognition method by units of voting or integration processing of a plurality of detectors, a method of adjusting weights of votes has also be proposed. For example, Japanese Patent Laid-Open No. 2008-204103 recognizes an entire image by integrating outputs of recognition devices by a plurality of tree structure filters. By recombining the recognition devices or by selecting weights at the time of integration, a whole recognition system is updated by being adapted to an environment.
Japanese Patent No. 03346679 detects quantized feature points from an input image and calculates a position and orientation of a target object using weighted generalized Hough transform from the obtained feature points. In this case, weights of feature points are calculated in advance from histograms of the feature amounts at the respective feature points.
Japanese Patent Laid-Open No. 2008-204103 prepares in advance weight variations of recognition devices, and selects a weight corresponding to the best detection result from their combinations. Since weight decision is discretely executed, a search speed and granularity of weight variations have a tradeoff relationship. Upon examination of recognition of a target object at an arbitrary orientation, feature amounts change depending on changes in viewpoint even for an identical portion on the target object.
When the method of Japanese Patent No. 03346679 is to be expanded to recognition of a target object at an arbitrary 3D orientation, it is difficult to decide vote weights from feature amount histograms.